IHD (CVD) Risk factors study: Clinical Project Research Paper

7/31/2019 IHD (CVD) Risk factors study: Clinical Project Research Paper

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Prevalence of Ischemic Heart Disease Risk Factors in Punjab

and

Application Statistical methods to predict Ischemic HeartDisease risk

Contributors:Ali Saleem Butt 5003-E, Ahmed Abdullah 596-E, Adil Suleman 5004-E,Hashim Ali 587-E, Qasim Zia 591-E

OthersMuhammad Zeeshan 578-E, Muhammad Naseem 597-E, Hassam

Tariq 594-E, Zuhaib Jaffer Malik 5011-E

University College of Pharmacy,

University of the Punjab, Lahore


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Risk Factor Prevalence & Risk PredictionPage 1

Abstract:This study was conducted to assess cardiovascular Risk factor

prevalence among different groups in our community and develop of riskassessment system through two different statistical methods. For this

purpose, Ischemic heart disease patients suffering from coronary arterydisease first time were observed. Data was collected from three differenthospitals by survey of patients individually. After collection, the data wasmanipulated Using Frequency distribution charts and highly valuableinformation was obtained that is helpful in directing the community healthservices and program into the key directions for getting better outcome inreducing IHD. For advanced analysis and derivation of a risk predictionsystem, the data was fitted into Logistic regression model and Classificationand Regression Model using SPSS 17 and R-Language. Logistic Regressionmodel when applied to readily observed patients data, there was a good81.3% correct prediction of disease development, though the factors

themselves in the model are not statistically significant. Classificationmodel was able to indicate a class with highest IHD risk which hadDiseased to Healthy ratio of 2.285. This study can serve as a foundationfor further research and paves a way for a more comprehensive study inthis respect in future.


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Introduction:Coronary heart disease, also called coronary artery disease or

ischemic heart disease, disease characterized by an inadequate supply ofoxygen-rich blood to the heart muscle (myocardium) because of narrowing

or blocking of a coronary artery by fatty plaques (see atherosclerosis). If theoxygen depletion is extreme, the effect may be a myocardial infarction(heart attack); if the deprivation is insufficient to cause infarction (death ofa section ofheart muscle), the effect may be angina pectoris, or spasms ofpain in the chest.[1]

Coronary Heart disease is the leading cause of deaths in all over theworld.

80% of the deaths due to CVD and 86% of the global burden of CVDare in the developing countries. Despite the high death rates due to non-communicable diseases, by 2010 the leading cause of death in thedeveloping countries including Pakistan would be CVD [2]. For planning

preventive and treatment strategies, the prevalence of the disease and itsrisk factors must be known. This study was therefore carried out todetermine the prevalence of ischemic heart disease in Pakistan as well asthat of its risk factors, so as the appropriate steps may be taken in order todecrease the occurrence of the disease in our community in future.

Therefore, study was carried out to determine the risk factorsinvolved in the development of ischemic heart disease in our localcommunity (Punjab).

Various risks Factors are involved in development of Ischemic Heart

diseaseThe following are confirmed independent risk factors for thedevelopment of CAD

1. Hypercholesterolemia (specifically, serum LDL concentrations2. Smoking3. Hypertension (high systolic pressure seems to be most significant in

this regard)4. Hyperglycemia (due to diabetes mellitus or otherwise)5. Type A Behavioural Patterns, TABP. Added in 1981 as an independent

risk factor after a majority of research into the field discovered that

TABP's were twice as likely to exhibit CAD as any other personalitytype.

6. Hemostatic Factors:[3] High levels of fibrinogen and coagulationfactor VII are associated with an increased risk of CAD. Factor VIIlevels are higher in individuals with a high intake of dietary fat.Decreased fibrinolytic activity has been reported in patients withcoronary atherosclerosis.

7. Hereditary differences/genetic polymorphisms in such diverse aspectsas lipoprotein structure and that of their associated receptors,enzymes of lipoprotein metabolism such as cholesteryl ester transferprotein (CETP) and hepatic lipase (HL),[4] homocysteineprocessing/metabolism, etc.
http://www.britannica.com/EBchecked/topic/165521/http://www.britannica.com/EBchecked/topic/258443/http://www.britannica.com/EBchecked/topic/258344/hearthttp://www.britannica.com/EBchecked/topic/138249/coronary-arteryhttp://www.britannica.com/EBchecked/topic/40908/atherosclerosishttp://www.britannica.com/EBchecked/topic/400432/http://www.britannica.com/EBchecked/topic/258429/heart-attackhttp://www.britannica.com/EBchecked/topic/287454/infarctionhttp://www.britannica.com/EBchecked/topic/95485/cardiac-musclehttp://www.britannica.com/EBchecked/topic/24631/angina-pectorishttp://en.wikipedia.org/wiki/Independent_risk_factorshttp://en.wikipedia.org/wiki/Hypercholesterolemiahttp://en.wikipedia.org/wiki/Low-density_lipoproteinhttp://en.wikipedia.org/wiki/Tobacco_smokinghttp://en.wikipedia.org/wiki/Hypertensionhttp://en.wikipedia.org/wiki/Hyperglycemiahttp://en.wikipedia.org/wiki/Type_A_personalityhttp://en.wikipedia.org/wiki/Coronary_artery_disease#cite_note-9http://en.wikipedia.org/wiki/Hereditaryhttp://en.wikipedia.org/wiki/Polymorphism_(biology)http://en.wikipedia.org/wiki/Cholesteryl_ester_transfer_proteinhttp://en.wikipedia.org/wiki/Cholesteryl_ester_transfer_proteinhttp://en.wikipedia.org/wiki/Hepatic_lipasehttp://en.wikipedia.org/wiki/Coronary_artery_disease#cite_note-pmid19810818-10http://www.britannica.com/EBchecked/topic/258443/http://www.britannica.com/EBchecked/topic/258344/hearthttp://www.britannica.com/EBchecked/topic/138249/coronary-arteryhttp://www.britannica.com/EBchecked/topic/40908/atherosclerosishttp://www.britannica.com/EBchecked/topic/400432/http://www.britannica.com/EBchecked/topic/258429/heart-attackhttp://www.britannica.com/EBchecked/topic/287454/infarctionhttp://www.britannica.com/EBchecked/topic/95485/cardiac-musclehttp://www.britannica.com/EBchecked/topic/24631/angina-pectorishttp://en.wikipedia.org/wiki/Independent_risk_factorshttp://en.wikipedia.org/wiki/Hypercholesterolemiahttp://en.wikipedia.org/wiki/Low-density_lipoproteinhttp://en.wikipedia.org/wiki/Tobacco_smokinghttp://en.wikipedia.org/wiki/Hypertensionhttp://en.wikipedia.org/wiki/Hyperglycemiahttp://en.wikipedia.org/wiki/Type_A_personalityhttp://en.wikipedia.org/wiki/Coronary_artery_disease#cite_note-9http://en.wikipedia.org/wiki/Hereditaryhttp://en.wikipedia.org/wiki/Polymorphism_(biology)http://en.wikipedia.org/wiki/Cholesteryl_ester_transfer_proteinhttp://en.wikipedia.org/wiki/Cholesteryl_ester_transfer_proteinhttp://en.wikipedia.org/wiki/Hepatic_lipasehttp://en.wikipedia.org/wiki/Coronary_artery_disease#cite_note-pmid19810818-10http://www.britannica.com/EBchecked/topic/165521/


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8. High levels ofLipoprotein(a),[5][6][7] a compound formed when LDLcholesterol combines with a substance known as Apoliprotein (a).

9. While detection of high levels of homocysteine has been linked tocardiovascular disease, lowering homocysteine levels may notimprove outcomes.[8]

Significant, but indirect risk factors include:

Lack ofexercise Consumption of alcohol Stress Diet rich in saturated fats\

Diet low in antioxidants Obesity Men over 60; Women over 65[9] A recent study done in India (Pondicherry) shows its association with

hemoglobin [10]

There are various risk assessment systems for determining the risk ofcoronary artery disease, with various emphases on different variablesabove. A notable example is Framingham Score, used in the FraminghamHeart Study. It is mainly based on age, gender, diabetes, total cholesterol,HDL cholesterol, tobacco smoking and systolic blood pressure.[11]

But information about some of these factors is occasionally not available.So, for the sake of this study only the factors about which the data isfrequently available in the society have been taken into account. Theseinclude direct as well as indirect factors like smoking, obesity, diabetes,anxiety, menopause, age, gender, body mass index, dietary fats, dailyactivity level, family history and hypertension.

Materials & MethodThe research design used was a simple survey in which the patients

fulfilling the patient selection criteria, from 3 major hospitals of Lahore,were approached and data was collected for analysis.

The detailed information was collected about all the social andmedical factors that contributed either directly or indirectly to developmentof Ischemic Heart Diseases. Then, the factors about which the information isgenerally and easily available in the community were isolated and based onthis information a survey form was developed for data collection.

Patient Selection Criteria and Total number of Cases Observed

The criteria for the selection of a patient, was set. It includes the followingpoints:
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1) The patient has any type of Ischemic Heart Disease as its finaldiagnosis

2) The patient has showed first symptoms of the disease within last 5years.

Data from 47 randomly selected patients who from the following hospitalswere collected:

1) Punjab Institute of Cardiology, Lahore2) Jinnah Hospital, Lahore3) Services Hospital, Lahore

First, the data was sorted and simple frequency distribution resultswere compiled using statistical analysis techniques i.e. frequencydistribution (among different categories) with the help of computersoftware SPSS 17 Statistics.

Statistical Analysis:

For more detailed insight of the data, advanced statistical techniqueswere used, including the determination of statistical significance of theindividual risk factors using:

Logistic Regression Model (using SPSS 17) Classification and Regression Tree (C&RT) method of data analysis

(using R language)

i) Binary logistic Regression Model:

We took Ischemic Heart Disease (I.H.D) as a dependent variable withtwo Categories (No or Yes) along with a mixture of independentvariables such as Age, Weight, Height, (weight and height were used tocalculate Body Mass Index ), Gender, Smoking History, Diet Fat, ActivityLevel, Anxiety, Family History Diabetes Mellitus (DM), Hypertension(HTN) and Menopause.

The age and BMI were taken as continuous variable while, SmokingHistory, Diet Fat, Activity Level, Anxiety, Family History Diabetes Mellitus(DM) and Hypertension (HTN) were taken as ordinal variable.Gender and Menopause were taken as nominal variables. Logistic

regression model was applied using SPSS 17and the results wereobtained and analyzed.

ii) Classification and Regression Trees:

The data was analyzed with Classification and Regression Tree (CART) usingR-Language as a tool and a class with the highest number of patients withleast number of factors involved was isolated. This class represents thepersons with the most risk of IHD.


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Results

Distribution of Risk Factors among different categories:

The data was collected and results were compiled to assess the prevalenceof IHD risk factors in the community. The following information wasrevealed:

1. The percentage distribution of risk factors (direct as well as indirect)among all the 47 IHD patients is as below:

2. The percentage distribution of risk factors (direct & indirect) amongmales and females in the observed patients group is as follows:

RiskFactor/Category

%age ofPatients

Male 71.74Female 28.26Age in 40s 30.43Age in 50s 67.39Smokers 39.13Diabetes 34.78Over Weight 34.78OBESE 21.74Dietary Fat 73.91Low Physical Activity 52.17Family History 47.83Hypertension 52.17Anxiety 54.35Edu. (Below matric) 39.13Edu. (matric -intermediate)

34.78

Edu. (Graduation &

Above)

21.74

Risk FactorFrequency(Gender wise)

Males(%age)

Females(%age)

Age in 40s 27.27 38.46

Age in 50s 69.69 61.53

Smokers 51.51 7.69Diabetes 30.3 46.15

Over Weight 39.39 23.07

OBESE 15.15 38.46

Dietary Fat 78.78 61.53Low PhysicalActivity 48.48 61.53

Family History 45.45 53.84

Hypertension 39.39 84.61

Anxiety 48.48 69.23Post

Menopausal 0 69.23


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3. Here are the percentage distribution of risk factors among differentage groups as observed from the patient data:

Risk factorsfrequency (Age

group wise)

40s(%age)

50s(%age)

60s &above(%age)

Male 64.286 78.5714 70.58

Female 35.714 21.4286 29.41

Smokers 28.571 28.5714 52.94

Diabetes 0 50 52.94

Over Weight 28.571 28.571 41.17

OBESE 28.571 21.43 17.64

Dietary Fat 78.571 71.4286 70.58

Low Physical Activity 35.714 50 64.7Family History 57.143 35.71 52.94

Hypertension 64.286 50 47.05

Anxiety 64.286 64.2 41.17

4. And these are the percentage distribution of risk factors amongdifferent education categories based on the data collected:

Risk factors frequencyUnderMatric(%age)

Matric toIntermediate

(%age)

Graduationor above(%age)

Male 66.67 75 80Female 33.33 25 20Age in 40s 38.88 25 30Age in 50s 55.55 75 70

Smokers 38.88 50 30Diabetes 11.11 56.25 30


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Coefficients (B) of Logit equation:

The coefficients (B) of Logit equation of the applied logistic regression

model for the relatively more significant factors i.e. hypertension, diabetes

and age, are all positive values. Coefficient of hypertension is 1.295 with

Odds ratio (represented by Exp(B) in the table) of 3.652 means that in

hypertensive persons there is 3.652 times higher risk of IHD. Similarly

Diabetes and age have coefficient value of 1.533 and 0.055 respectively.

The odds values of these factors show that the people with diabetes have

4.634 times more risk of IHD development and 1.057 times additional risk

for each year of age.

The Model

With coefficient values given above, the logit equation can be written as:Logit = Z = - 9.075 + Age * 0.055 + Gender * 3.021 + Smoking * 0.848 +Diabetes * 1.533 + BMI * 0.078 + Dietary Fats * .374 + ActivityLevel * -.313+ FamilyHistory * .601 + Hypertension * 1.295 + Anxiety * -.578 +Menopause * 0.491

Risk Factor Value

Age Age in years

Gender Male =0 Female = 1

Smoking Present = 1 Absent = 0

Diabetes Present = 1 Absent = 0

BodyMassIndex BMI value

DietFats Low = 1 Moderate =2 High =3

ActivityLevel Low = 1 Moderate =2 High =3

FamilyHistory Present = 1 Absent = 0

Hypertension Present = 1 Absent = 0

Anxiety Present = 1 Absent = 0

MenoPause Present = 1 Absent = 0

Z value is then put into the following function, P(IHD) = ez / (1+ez) thatgives the probability of IHD in any particular case.

Performance of the model:

When the model is applied to the recorded cases, the following casedistribution chart is obtained.


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According to the model and as depicted in the chart above, there is a

mild degree of miss classification (18.7% of the observed cases) when it isapplied to the data. So, the model can predict the disease probability in thepeople but not very reliably. The reasons for the insignificance of resultscan be:

1. Inadequate data (too small sample size)2. Biasing during data collection (Not random fully representative

sample)3. Some other statistical model could have been used e.g. Simultaneous

Equation Model


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Classification and Regression Tree: (CART)

Using R language as the tool, the data was analyzed and the followingclassification tree was obtained.


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Explanation:


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Among total 56 persons were observed. 46 persons were diseased and 10patients were healthy. At each level, there is a condition (decision).The right branch represents the negative class i.e. the condition is notmet for the cases in that class, and the left branch represents positiveclass i.e. for which the condition is met.

At first level, the data is split into two classes based on the condition:

Age is smaller than 30.5 years (Age > 30.5 years)

Positive class on the left has 3 (30% of the total healthy individuals) healthypersons and 0 (0% of the total diseased persons) diseased persons.The negative class on the right has 7 healthy persons (70% of thetotal healthy persons) and 46 diseased persons (100% of the totaldiseased persons).

At second level, the right class (negative class) with respect to diseasedpersons is split into further classes based on the condition:

Activity Level is larger than or equal to 1.5 (Activity Level >= 1.5)

Or

Activity level = Moderate or High

Positive class on the left has 6 (60% of the total healthy individuals) healthypersons and 22 (47.8% of the total diseased persons) diseasedpersons. The negative class on the right has 1 healthy person (10% of

the total healthy persons) and 24 diseased persons (52.2% of thetotal diseased persons).

At third level, the left hand class (Positive class) is further sub classifiedbased on the condition:

Age is more than or equal to 68.5 years (Age >68.5 years)

Positive class on the left has 2 healthy persons (20% of the total healthyindividuals) and 0 diseased persons (0 % of the total diseasedpersons). The negative class on the right has 4 healthy person (40%

of the total healthy persons) and 22 diseased persons (47.8% of thetotal diseased persons).

At fourth level, the right hand class having 40% healthy and 47.8%diseased persons is further split in order to get maximum separationbetween the diseased and the healthy persons, using the followingcriteria:

Hypertension duration above or equal to 7.5 years (Hypertension duration>= 7.5 years)


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Positive class on the left has 2 (20% of the total healthy individuals) healthypersons and 1 (2.2% of the total diseased persons) diseased persons.The negative class on the right has 2 healthy person (20% of the totalhealthy persons) and 21 diseased persons (45.7% of the totaldiseased persons).

Classification tree shows, only three factors are significant, namely Age,Hypertension duration and Activity Level.


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Discussion

By analyzing the distribution of risk factors we conclude the followingimportant points:

The most prevalent risk factor overall for IHD in the community is HighDietary Fat Intake as it is present in 74 percent of the IHD patients.So, generally, in order to improve community health, efforts must bemade to lower the prevalence of high fat intake in the individuals.Public awareness campaigns have to be directed primarily in thisdirection to reduce the probability of IHD in the communitysignificantly.

The second highest occurrence belongs to Anxiety that is there in 54.35percent of the patients. It is the secondary concern, especially in the

perspective of current social atmosphere in the society whereprevalence of anxiety, mostly generalized anxiety disorder hastremendously increased. And the fact that it is the most neglecteddisorder that is rarely diagnosed, given importance and treated as adisease, makes the circumstances even more critical. Although theanxiety was not proved to be significant factor in this study, it can bea significant contributor to the IHD cases in the community as awhole due to its high prevalence and already proved significance asIHD risk factor.

The other factors i.e. Hypertension (52.17%), Low Physical Activity (52.17%)

and Family History (47.83%) are also present in comparatively higherfrequency and can be important reasons for increasing number of IHDcases day by day.

Male vs Female Patients:

This comparison shows some very interesting facts about the riskfactors distribution among genders.

1. Hypertension is the most prevalent risk factor among femalepatients (84.61%) while in males, it contributes in merely 39.39 %of IHD patients.

2. Anxiety and Obesity are also more prevalent in females (69.23%and 38.46% respectively) than in males (48.48 % and 15.15%respectively of the total male cases).

3. Female patients that are diabetic as well are 46.15% while thoseof men are 30.3%, showing high precedence of diabetes infemales than in males leading to IHD.

4. The high number of postmenopausal women (69.23% of totalFemale patients) is also indicative to the proposed fact thatmenopause poses an additional risk of IHD to females.

5. The only significant factor present in high frequency in males

compared to females is smoking. (51.51% males and 7.69%females)


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Patients among Different Age groups:

Most of the risk factors are equally distributed among the three differentage group categories (i.e. patients in 40s, patients in 50s and patients in60s or above). Some of the important outcomes are as follows:

1. The frequency of low physical activity increases with theincreasing age group. So, with advancing age, there is usually lowphysical activity that can add to the risk of IHD.

2. Hypertension and anxiety are more prevalent in younger agegroups i.e. 40s and 50s groups. It signals that there can be acorrelation among these two factors. Moreover, the high frequencyof anxiety among 40s patients (64.29%) compared to the 60s orabove patient group (41.17%) indicates the high stress life stylesspecially in younger persons who are more often indulged inworking and earning issues than the seniors in our community.

3. A positive smoking history is more prevalent among the senior age

group patients, in 60s and above (52.94%) compared to the28.57% in patients in 40s and 28.57 % in those in 50s. It can beinterpreted as the hypothetical statement that smoking has a slowbut continuously mounting with time effect on IHD developmentthat results in IHD in later in age.

Patient Risk Factor Prevalence (Education wise):

The percentage frequency chart of risk factors among different educationcategories shows these significant results.

1. Anxiety is present in 90% of the patients with graduation or above

education, compared to the 44.44% and 43.75% in undermatricand from matric to intermediate groups respectively. It shows thatanxiety being more common in highly educated individual that canbe attributed to their more mental stressing nature of job, can bemajor contributing factor in this group. It also indicates a need tocounsel that group to change their life styles with a target tolessen the anxiety and thus, IHD risk.

2. Family history is also more common among the graduation orabove group being present in 80% of the patients while forundermatric and matric to intermediate groups the percentages

are 38.88% and 31.25% respectively. One possible reason to sucha conclusion is more awareness of the educated group about theIHD and thus, their better ability to identify and indicate a positivefamily history during data survey than those with less education.

Advanced Statistical Analysis:

Binary Logistic Regression Model:

When Binary Logistic Regression Model was fitted into the data the resultsshows that no factor comes out to be significant. The factors with relativelymore significance compared to the other are Hypertension (significancevalue = 0.115), Diabetes (significance value = 0.135) and Age (significancevalue = 0.148).


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The other factors like smoking, gender, body mass index, dietary fats, dailyactivity level, family history, menopause and anxiety level have proven tobe strongly associated with IHD development in a number of researchpapers, but they come out to be very less significant in the model appliedhere.

There is no factor that is significant enough statistically. The reasons canbe:

1. There is relatively weaker relationship between these variables andIHD pathogenesis compared to the other variables (i.e. Age,hypertension, gender and menopause) that come out to be significant

2. As the significance of statistic not only depends on the strength ofrelationship between two variables but also on the number ofobservations made, in-sufficient data can be the other possiblereason for such results.

3. The data obtained may not be an ideal representative random sample

of the population and may have been influenced by biasing,especially during incorporation of data of healthy persons.

The distribution chart of observed groups and their predicted diseaseprobabilities shows a mild degree of miss classification (18.7%) whichshows that despite of insignificance of the results, the logistic regressionequation derived by fitting the model is able to predict the disease withmoderate precision.

Classification and Regression Model:

By applying this model, only three factors come out as significant i.e.Age, Hypertension duration and Activity Level.

It also shows that the class at highest risk of IHD is the one with:1: age above 30.5 years and less than or equal to 68.5 years2: activity level moderate or high3: hypertension for more than or equal to 7.5 years

Because here the percentage of healthy persons is 20% while that ofdiseased is 45.7%. The ratio of diseased to healthy persons for this class is2.285 showing significant high risk in this class for IHD.

Conclusion:The frequency distribution of IHD risk factors among different

categories shows many important findings about the risk factors prevalencein the community. It directs us to the areas among specific groups in thecommunity requiring special workout in order to control the IHD prevalence.Having targets pointed out, better results can be obtained from communityhealth awareness programs to decrease IHD cases in the days to come.

Although the advanced statistical analysis has not produced veryappreciable results, this study can serve as a foundation for furtherresearch and paves a way for a more comprehensive study in this respect.


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